Welcome to the US Department of Labour's interactive Workforce Gender Ratio and GDP per Capita demo! In this demo, we will be exploring the relationship between the ratio of men to women in the workforce and its impact on the GDP per capita each state.
Throughout the US, men dominate the workforce in every state, with some states such as Utah having as high as 60% of their workforce dominated by men. However, we want to explore how changes in this ratio may or may not affect the financial output of each state. In order to accomplish this, we have devised two visually interactive tools alongside a mathematical analysis of these values to determine whether or not there is a correlation between these values.
The data for this project has been sourced from the National Database of Childcare Prices from ourselves, the Department of Labour (https://www.dol.gov/agencies/wb/topics/featured-childcare). In addition, we have utilized a public Kaggle dataset of US populations by state (https://github.com/jakevdp/data-USstates/blob/master/state-population.csv) and a dataset from the USA's Bureau of Economic Analysis that contains the GDP per state (https://www.bea.gov/data/gdp/gdp-state). By combining this data, we aim to generate statistical analysis alongside interactive visual demos that are able to clearly demonstrate the correlation, or lack thereof, between GDP per capita and the gender ratio in the workforce of each state.
Below is an interactive map that demonstrates the per capita GDP of each state and generates a plot of its ratio of males to females within its workforce. Each chart also contains the national ranking of the state based on its per capita GDP.
- Note: Per-capita GDP refers to the GDP of the state divided by its population, which is a figure that is more representative of the money earned by the state without being influenced by the state's population size, which can cause larger states to show disproportionately higher GDP's in this context.
- In many official documentations, District of Columbia (commonly known as Washington DC, or the district where the White House resides) is considered as a state since it is techinically neither part of a state nor a state itself. For the purposes of this project, we will not be considering District of Columbia as its own state.
As our above interactive figure demonstrates, just about every state has a relatively equal workforce ratio, with the most notable outlier being Utah, which has the lowest percentage of female earners at 39.5%. Additionally, Florida stands out as the state with the highest percentage of female earners at 46.7%. Below, we have generated a scatterplot that demonstrates the income ratio of each state on the y-axis and the GDP per capita of the state on the x-axis. If there is a notable correlation between the two, we would see the graph have a general trend going either upwards or downwards. However, if we see little to no noticeable trend, it is likely that there is either no correlation or an extremely weak correlation.
From the above figure, there does not seem to be a noticeable trend, as the shape of the scatterplot is mostly uniform, with Utah being the largest discrepancy, having a high ratio of men to women in their workforce, and an average GDP per capita.
To mathematically explore this relationship, we can utilize the Spearman's rank correlation coefficient, which is a metric used to analyze the correlation between two continuous variables. This will give us a more holistic sense of how the relationship between these two variables plays out.
Spearman ρ = -0.0228, p-value = 0.8751
From our interactive demos, it has become apparent that there appears to be no correlation between the ratio of men to women within the workforce and the GDP per capita of the state. A ρ value of -0.0228 is very close to 0, and implies no distinct positive or negative correlation between these two values. Additionally, our p-value of 0.8751 is very large, and leads us to conclude that we cannot reject the null hypothesis, and there is no significant correlation between these two values.
Conclusions¶
From our visual figures, we can see that most states have fairly similar workforce ratios, and that the GDP per capita of states does not appear to reflect their workforce distribution. Our interactive map has displayed the specific breakdown of each state's GDP per capita alongside it's workforce gender ratio, and our interactive scatterplot has demonstrated a visually uniform distribution between these two variables. Finally, calculating our Spearman's rank correlation coefficient has resulted in a close-to-zero value for ρ, and a p-value of 0.8751, both indicitive of our inability to reject our null hypothesis, which is that there is no significant correlation between the per capita GDP of a state and it's ratio of men to women in the workforce.
As a result, our study is very confident that the ratio of men to women in the workforce does not display any direct correlation to the financial output of any single state. The two states with the highest and lowest gender workforce ratios, Utah and Florida, are both right around the median GDP value for the entire nation, as shown in the scatterplot. Additionally, the two states with the highest and lowest GDP per capita, New York and Mississippi, have relatively equal workforce ratios of 1.19 and 1.23. Therefore, our recommendation to the Department of Labour and associated federal bodies is to minimize any focus on this workforce ratio solely when it comes to increasing financial output. Of course, this does not at all mean that programs intended to increase the participation of females in the workforce are at all misguided; such programs are imperative to the operation of our nation in a way that is both accepting of all and diverse in its work. Rather, that we are not inclined to say one way or another that such programs would directly impact financial output, or more specifically, GDP per capita.